function performance_vector = feature_performance( input, output, numer_of_neurons )
% FEATURE_PERFORMANCE : This function calculates features performance
% INPUT :   net Net to create and train ,
%           input matrix tu be used as net input
%           output vector used as network desired output
%  OUTPUT : vector where elements represent the perfermonces of network
%            trained without the feature of that index

%FIRST : CREATE OUTPUT VECTOR 
[ row_count, column_count ] = size(input);
performance_vector = zeros(1,column_count);

%SECOND : ITERATION 
%        1. Create temporary input vector deleting the feature of index i
%        2. Create and train the network withe the temp input
%        3. Save network performance in the output at index i

for i=1:column_count,
    temp_input = input;
    temp_input(:,i)=[];
    [temp_net, temp_tr ] = create_fit_net(temp_input',output',numer_of_neurons);
    performance_vector(1,i) = temp_tr;
end
